Systems and methods for providing object recognition based on detecting and extracting media portions

ABSTRACT

Systems, methods, and non-transitory computer-readable media can receive a selection of an image. An object included in the image can be detected. An image portion that includes the object can be extracted from the image. The image portion can be provided for image analysis based on one or more object recognition processes. An identifier for the object can be received. The identifier can be determined based on the one or more object recognition processes being applied to the image portion.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/656,276, filed on Mar. 12, 2015 and entitled “SYSTEMS AND METHODS FORPROVIDING OBJECT RECOGNITION BASED ON DETECTING AND EXTRACTING MEDIAPORTIONS”, which is incorporated herein by reference.

FIELD OF THE INVENTION

The present technology relates to the field of media processing. Moreparticularly, the present technology relates to techniques for providingobject recognition based on detecting and extracting media portions.

BACKGROUND

Today, people often utilize computing devices (or systems) for a widevariety of purposes. Users can use their computing devices to, forexample, interact with one another, create content, share information,and access information. In some instances, a user of a computing devicecan utilize a camera or other image sensor of the computing device (orsystem) to capture or record media content, such as images and/orvideos.

In some cases, media content such as images can be processed, such aswhen the images are uploaded to a social networking system. Imageprocessing applied to images can, for example, be utilized to acquireinformation about the images. Under conventional approaches, imageprocessing can often require significant amounts of computer processingpower, time, data consumption, as well as manual effort. As such,conventional approaches can be inefficient, expensive, and inconvenient.Due to these and other reasons, conventional approaches can createchallenges for or reduce the overall user experience associated withutilizing computing devices (or systems) to interact and engage withmedia content, such as images.

SUMMARY

Various embodiments of the present disclosure can include systems,methods, and non-transitory computer readable media configured toreceive a selection of an image. An object included in the image can bedetected. An image portion that includes the object can be extractedfrom the image. The image portion can be provided for image analysisbased on one or more object recognition processes. An identifier for theobject can be received. The identifier can be determined based on theone or more object recognition processes being applied to the imageportion.

In an embodiment, the image and the identifier can be presented. One ormore options to modify at least one of the identifier or informationassociated with the image can be provided. An upload command to uploadthe image can be received. The image and the identifier can betransmitted subsequent to receiving the upload command.

In an embodiment, detecting the object included in the image can furthercomprise determining a location of the object within the image. Theidentifier can be presented based on the location of the object withinthe image. The identifier can be presented to appear to overlay theimage. The identifier can be presented to avoid obscuring the objectincluded in the image.

In an embodiment, a second object included in the image can be detected.A second image portion that includes the second object can be extractedfrom the image. The second image portion can be provided for imageanalysis based on the one or more object recognition processes. Theimage portion and the second image portion can be provided inconjunction.

In an embodiment, the one or more object recognition processes can beperformed, at least in part, via one or more remote servers.

In an embodiment, the object can include a face of a user represented inthe image. The one or more object recognition processes can include oneor more facial recognition processes. The identifier can include a nameassociated with the user.

In an embodiment, the one or more facial recognition processes canutilize, at least in part, one or more people clustering processes.

In an embodiment, the selection of the image can be received from anuploading user. The uploading user can be associated with a set ofsocial connections via a social networking system. The one or morefacial recognition processes can utilize, at least in part, one or moreface models associated with a subset of social connections out of theset of social connections.

In an embodiment, the subset of social connections can include aspecified quantity of highest ranked social connections. Each socialconnection in the set can be ranked based on at least one of a socialcoefficient metric for each social connection relative to the uploadinguser, a social affinity metric for each social connection relative tothe uploading user, a social interaction recency metric for each socialconnection relative to the uploading user, or location data associatedwith each social connection.

In an embodiment, the identifier can be utilized, at least in part, todefine a set of images such that each image in the set includes arespective object associated with the identifier.

It should be appreciated that many other features, applications,embodiments, and/or variations of the disclosed technology will beapparent from the accompanying drawings and from the following detaileddescription. Additional and/or alternative implementations of thestructures, systems, non-transitory computer readable media, and methodsdescribed herein can be employed without departing from the principlesof the disclosed technology.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example system including an example media portionrecognition module configured to facilitate providing object recognitionbased on detecting and extracting media portions, according to anembodiment of the present disclosure.

FIG. 2A illustrates an example object detection module configured tofacilitate detecting and extracting media portions, according to anembodiment of the present disclosure.

FIG. 2B illustrates an example transceiver module configured tofacilitate providing object recognition based on detecting andextracting media portions, according to an embodiment of the presentdisclosure.

FIG. 3 illustrates an example scenario associated with providing objectrecognition based on detecting and extracting media portions, accordingto an embodiment of the present disclosure.

FIG. 4 illustrates an example scenario associated with providing objectrecognition based on detecting and extracting media portions, accordingto an embodiment of the present disclosure.

FIG. 5 illustrates an example method associated with providing objectrecognition based on detecting and extracting media portions, accordingto an embodiment of the present disclosure.

FIG. 6 illustrates an example method associated with providing objectrecognition based on detecting and extracting media portions, accordingto an embodiment of the present disclosure.

FIG. 7 illustrates a network diagram of an example system including anexample social networking system that can be utilized in variousscenarios, according to an embodiment of the present disclosure.

FIG. 8 illustrates an example of a computer system or computing devicethat can be utilized in various scenarios, according to an embodiment ofthe present disclosure.

The figures depict various embodiments of the disclosed technology forpurposes of illustration only, wherein the figures use like referencenumerals to identify like elements. One skilled in the art will readilyrecognize from the following discussion that alternative embodiments ofthe structures and methods illustrated in the figures can be employedwithout departing from the principles of the disclosed technologydescribed herein.

DETAILED DESCRIPTION Providing Object Recognition Based on Detecting andExtracting Media Portions

People use computing devices (or systems) for a wide variety ofpurposes. Computing devices can provide different kinds offunctionality. Users can utilize their computing devices to produceinformation, access information, and share information. In someinstances, computing devices can include or correspond to camerascapable of capturing or recording media content, such as images orvideos. In some cases, computing devices can view, access, download, andsave such media content.

In one example, a user of a social networking system can utilize his orher computing device to upload a media content item, such as an image,to the social networking system. The image can include, depict, orrepresent one or more persons. For instance, the image can include avisual representation of a person, such as when the image depicts theperson's face. Conventional approaches to media processing can sometimesrequire manual effort in order to recognize objects (e.g., the person'sface) included, depicted, or represented in the image. Such conventionalapproaches can, for instance, require a manual tap or click with respectto the person's face object in the image and then a manual selection orinput indicating to whom the face belongs. Further, in some cases,conventional approaches can utilize facial recognition processes ortechniques to analyze the entire image to identify the person whose faceis included in the image. However, such conventional approaches canrequire significant processing power, time, and/or data consumption.

As such, conventional approaches can be inconvenient, inefficient,and/or expensive. Therefore, an improved approach can be beneficial foraddressing or alleviating various concerns associated with conventionalapproaches. The disclosed technology can provide object recognitionbased on detecting and extracting media portions. Various embodiments ofthe present disclosure can receive a selection of an image. An objectincluded in the image can be detected. An image portion that includesthe object can be extracted from the image. The image portion can beprovided for image analysis based on one or more object recognitionprocesses. An identifier for the object can be received. The identifiercan be determined based on the one or more object recognition processesbeing applied to the image portion. It is contemplated that there can bemany variations and/or other possibilities.

FIG. 1 illustrates an example system 100 including an example mediaportion recognition module 102 configured to facilitate providing objectrecognition based on detecting and extracting media portions, accordingto an embodiment of the present disclosure. As shown in the example ofFIG. 1, the media portion recognition module 102 can include a mediaselection module 104, an object detection module 106, and a transceivermodule 108. In some instances, the example system 100 can include atleast one data store 110. The components (e.g., modules, elements, etc.)shown in this figure and all figures herein are exemplary only, andother implementations may include additional, fewer, integrated, ordifferent components. Some components may not be shown so as not toobscure relevant details.

In some embodiments, the media portion recognition module 102 can beimplemented, in part or in whole, as software, hardware, or anycombination thereof. In general, a module as discussed herein can beassociated with software, hardware, or any combination thereof. In someimplementations, one or more functions, tasks, and/or operations ofmodules can be carried out or performed by software routines, softwareprocesses, hardware, and/or any combination thereof. In some cases, themedia portion recognition module 102 can be implemented, in part or inwhole, as software running on one or more computing devices or systems,such as on a user or client computing device. For example, the mediaportion recognition module 102 or at least a portion thereof can beimplemented as or within an application (e.g., app), a program, or anapplet, etc., running on a user computing device or a client computingsystem, such as the user device 710 of FIG. 7. In another example, themedia portion recognition module 102 or at least a portion thereof canbe implemented using one or more computing devices or systems thatinclude one or more servers, such as network servers or cloud servers.In some instances, the media portion recognition module 102 can, in partor in whole, be implemented within or configured to operate inconjunction with a social networking system (or service), such as thesocial networking system 730 of FIG. 7. It should be understood thatthere can be many variations or other possibilities.

The media selection module 104 can be configured to facilitate receivinga selection of a media content item, such as an image (e.g., photo,picture, video still frame, animated image, etc.) or a video (e.g., aplurality of video still frames with or without audio). In some cases, auser of a computing device (or system) and/or a social networking system(or service) can provide the selection of the media content item, suchas the image (or video, etc.), which can be received by the mediaselection module 104. In one example, the user can select the image foruploading, downloading, sharing, posting, publishing, transmitting,and/or other purposes. In some instances, the image selection receivedby the media selection module 104 can be provided by an image selectionprocess, such as a random image selection algorithm or a recentlyacquired image selection algorithm. It should be understood that manyvariations are possible.

The object detection module 106 can be configured to facilitatedetecting an object included in the image. The object detection module106 can also be configured to facilitate extracting, from the image, animage portion (or patch, area, etc.) that includes the object. Moredetails regarding the facial recognition module 106 will be providedbelow with reference to FIG. 2A.

The transceiver module 108 can be configured to facilitate providing theimage portion for image analysis based on (i.e., based at least in parton) one or more object recognition processes. The transceiver module 108can further be configured to facilitate receiving an identifier for theobject. The identifier can be determined based on the one or more objectrecognition processes being applied to the image portion. Thetransceiver module 108 will be discussed in more detail with referenceto FIG. 2B.

Furthermore, in some implementations, the media portion recognitionmodule 102 can be configured to communicate and/or operate with the atleast one data store 110, as shown in the example system 100. The atleast one data store 110 can be configured to store and maintain varioustypes of data. In some implementations, the at least one data store 110can store information associated with the social networking system(e.g., the social networking system 730 of FIG. 7). The informationassociated with the social networking system can include data aboutusers, social connections, social interactions, locations, geo-fencedareas, maps, places, events, pages, groups, posts, communications,content, feeds, account settings, privacy settings, a social graph, andvarious other types of data. In some implementations, the at least onedata store 110 can store information associated with users, such as useridentifiers, user information, profile information, user locations, userspecified settings, content produced or posted by users, and variousother types of user data. In some embodiments, the at least one datastore 110 can store information that is utilized by the media portionrecognition module 102. For instance, the at least one data store 110can store information about images as well as information useful forobject detection and object recognition. It is contemplated that therecan be many variations or other possibilities.

In one example, the user of the social networking system can utilize hisor her computing system to post, share, and/or send media content viathe social networking system. In this example, the user can select animage to be uploaded for posting, sharing, and/or sending via the socialnetworking system. The user's selection of the image can be received bythe media selection module 104. The object detection module 106 can thenapply one or more face object detection processes (i.e., face detectionprocesses, facial detection processes, etc.) to the image in order todetect any face objects included, represented, and/or depicted in theimage.

Continuing with the example, the image can include, represent, and/ordepict a face of a social connection or friend of the user within thesocial networking system. The object detection module 106 can detect,based on the face object detection processes, the face object of thesocial connection or friend included in the image. Additionally, theobject detection module 106 can also extract, from the image, acorresponding image portion that includes the face object. Thetransceiver module 108 can provide the image portion for image analysisbased on one or more object recognition processes, such as one or moreface object recognition processes (i.e., face recognition processes,facial recognition processes, etc.). The transceiver module 108 cansubsequently receive an identifier determined for the object based onthe one or more object recognition processes being applied to the imageportion. In this example, the identifier can correspond to a name (e.g.,username, account name, etc.) of the user's social connection or friendwhose face is included in the image. Furthermore, in this example, theidentifier can be in the form of a tag including the name of user'ssocial connection or friend. The identifier (e.g., tag) can beautomatically provided in association with the image. If the user sochooses, when he or she initiates the uploading of the image forposting, sharing, and/or sending, the identifier can be included in theimage uploading process.

In another example, a second object included in the image, such as aface object associated with another social connection or friend of theuser, can be detected by the object detection module 106. A second imageportion that includes the second object can be extracted from the imageby the object detection module 106. The second image portion can beprovided, by the transceiver module 108, for image analysis based on theone or more object recognition processes. In some cases, the imageportion and the second image portion can be provided, in conjunction,for image analysis. Moreover, in this example, a second identifier inthe form of a second tag including the name of user's other socialconnection or friend can be received. When the users initiates theuploading of the image for posting, sharing, and/or sending, the secondidentifier can be included as well. It should be appreciated that theexamples herein are provided for illustrative purposes and that manyvariations are possible.

FIG. 2A illustrates an example object detection module 202 configured tofacilitate detecting and extracting media portions, according to anembodiment of the present disclosure. In some embodiments, the objectdetection module 106 of FIG. 1 can be implemented as the example objectdetection module 202. As shown in FIG. 2A, the object detection module202 can include an object location determination module 204 and a mediaportion extraction module 206.

As discussed previously, the object detection module 202 can beconfigured to facilitate detecting an object included in an image. Insome cases, the object detection module 202 can utilize one or moreobject detection processes to detect any objects in the image. Forinstance, the object detection module 202 can utilize one or more faceobject detection processes to detect the presence of any face objects orfaces included (i.e., represented, depicted, shown, displayed, etc.) inthe image. In some cases, object detection processes applied to anentire image can be more efficient and/or can require less resources(e.g., processing power, time, data consumption, etc.) than objectrecognition processes applied to the same entire image. This can bebecause object detection processes are generally configured to detectwhether or not any defined (or predefined) objects are present in theimage, while object recognition processes are generally configured torecognize or identify any defined (or predefined) objects in the image.

In some embodiments, detecting the object included in the image canfurther comprise determining a location of the object within the image.The object location determination module 204 can be configured todetermine the location of the object within the image. In some cases,the object location determination module 204 can determine or identify aset of pixels of the image that includes the object. The set of pixelscan, for example, form or correspond to a particular image portion,image patch, or image area, etc. In one example, the object locationdetermination module 204 can determine where in the image any faces ofpeople are located. The object location determination module 204 candetermine one or more sets of pixels or one or more image portions thatinclude one or more detected faces.

Furthermore, the object detection module 202 can utilize the mediaportion extraction module 206 to facilitate extracting, from the image,an image portion that includes a detected object. The media portionextraction module 206 can, for instance, extract a copy of the imageportion or set of pixels that includes the detected object. In oneexample, the media portion extraction module 206 can extract arespective image portion (or a respective copy thereof) that includeseach face detected in the image. It should be appreciated that there canbe many variations or other possibilities.

FIG. 2B illustrates an example transceiver module 252 configured tofacilitate providing object recognition based on detecting andextracting media portions, according to an embodiment of the presentdisclosure. In some embodiments, the transceiver module 108 of FIG. 1can be implemented as the example transceiver module 252. As shown inFIG. 2B, the transceiver module 252 can include a media portiontransmitting module 254 and an object identifier receiving module 256.

In some embodiments, the transceiver module 108 can utilize the mediaportion transmitting module 254 to transmit, send, or provide an imageportion of a detected object for image analysis based on one or moreobject recognition processes. As discussed previously, in some cases,object recognition processes can require more resources and/or are morecomputationally intensive than object detection processes. As such, thedisclosed technology can use the object detection processes to detectobjects and then extract image portions of any detected objects. Theextracted image portions can then be provided, such as by the mediaportion transmitting module 254, to be analyzed based on the objectrecognition processes. Therefore, instead of applying the objectrecognition processes to one or more entire images, the objectrecognition processes can be applied to only one or more image portions.This can save resources and allow the object recognition processes to beperformed more efficiently.

In some implementations, the one or more object recognition processescan be performed, at least in part, via one or more remote servers. Inone example, one or more face object recognition processes can beperformed via one or more servers of a social networking system orservice (e.g., the social networking system 730 of FIG. 7). It iscontemplated that many variations are possible. For instance, in somecases, the object recognition processes can be performed by the samecomputing device(s) or system(s) that performs the object detectionprocesses. In some embodiments, one or more identifiers for objects(e.g., identifiers for face objects) can be provided from the one ormore remote servers to the computing device (or system) that transmittedor provided the image to the remote servers. The one or more remoteservers can provide options or suggestions to the computing deviceregarding who or what is depicted in the image. In some cases, if theobject recognition processes determines equal or substantially similar(i.e., similar within an allowable deviation) recognition confidencescores for multiple possible recognitions, then the computing device canbe presented with (e.g., from the remote servers) at least one optionalor suggested identifier for each of the multiple possible recognitions.For example, if one or more face recognition processes, applied to agiven face, determines equal or substantially similar recognitionconfidence scores for Person X, Person Y, and Person Z, then thecomputing device can be presented with an optional or suggestedidentifier (e.g., tag, name) for each of Person X, Person Y, and PersonZ.

Furthermore, in some embodiments, the transceiver module 108 can utilizethe object identifier receiving module 256 to receive an identifier forthe object. The identifier can, for example, be determined based on theone or more object recognition processes being applied to the providedimage portion. In some cases, the identifier can correspond to a tag ora marker that indicates a name or a label associated with the object,which has been recognized based on the one or more object recognitionprocesses. Again, there can be many variations or other possibilities.

FIG. 3 illustrates an example scenario 300 associated with providingobject recognition based on detecting and extracting media portions,according to an embodiment of the present disclosure. The examplescenario 300 illustrates a client 302, such as a client computing deviceor system, and a server(s) 304.

As shown in the example of FIG. 3, an image 306 can be selected at theclient 302. The image 306 can include (i.e., represent, depict, show,display, etc.) a face 308 of a user. In this example, one or more faceobject detection processes can be performed at the client 302 to detectthe user's face or face object 308. Having detected the face object 308,an image portion 310 including the face object 308 can be extracted fromthe image 306. The client 302 can then provide or transmit the imageportion 310 to the server(s) 304. The server(s) 304 can perform one ormore face object recognition processes with respect to the image potion310 to recognize the face object 308 and determine an identifier 312 forthe face object 308. The server(s) 304 can then transmit the identifier312 to be received at the client 302. Many variations are possible.

FIG. 4 illustrates an example scenario 400 associated with providingobject recognition based on detecting and extracting media portions,according to an embodiment of the present disclosure. The examplescreenshot 400 illustrates an example interface 402, such as a userinterface of an application utilizing or otherwise associated with thedisclosed technology.

As shown in FIG. 4, the example interface 402 can enable a first user404 to select an image 406 to be uploaded, posted, shared, sent, and/orotherwise processed at a social networking system. The image 406 caninclude a second user, such as a friend or social connection of thefirst user 404. In particular, the image 406 can include the seconduser's face 408.

In this example scenario 400, subsequent to a selection of the image 406by the first user 404, the second user's face or face object 408 can bedetected during face detection. An image portion including the seconduser's face object 408 can be provided for image analysis based on facerecognition. In this example, an identifier 410 can be determined basedon the face recognition. The identifier 410 can indicate a name of thesecond user (“John Doe”). In some instances, the image 406 and theidentifier 410 can be presented, as shown. One or more options to modifyat least one of the identifier 410 or information associated with theimage 406 can also be provided. The one or more options can include anoption 412 to remove the identifier 410. Moreover, an upload command toupload the image can be received, such as when the first user 404 clickson, taps on, or otherwise interacts with the “Post” button. In someinstances, the identifier for the second user, the name of the seconduser, a tag associated with the second user, and/or the one or moreoptions, etc., can be presented before the first user 404 clicks on,taps on, or otherwise interacts with the “Post” button. In some cases,the image 406 and the identifier 410 can be transmitted subsequent toreceiving the upload command.

Moreover, in some cases, a location of the face object 408 within theimage 406 can be determined, such as during face detection. Theidentifier 410 can be presented based on the location of the face object408 within the image 406. As shown in the example scenario 400, theidentifier 410 can be presented to appear to overlay the image 406 andcan be presented to avoid obscuring the face object 408 included in theimage 406.

As discussed, the selection of the image 406 can be received from thefirst user 404 (i.e., an uploading user). The uploading user 404 can beassociated with a set of social connections via the social networkingsystem. For instance, the uploading user 404 can have a list of friendsvia the social networking system. In some embodiments, facialrecognition processes applied to provided image portions can utilize, atleast in part, one or more face models or face templates associated witha subset of social connections out of the set of social connections. Insome implementations, the subset of social connections can include aspecified quantity of highest ranked social connections (e.g., the top50 friends closest to the uploading user 404, the top 100 friends whohave recently interacted with the uploading user 404, the top 220friends who have the most social interactions with the uploading user404, etc.). Each social connection in the set can be ranked based on atleast one of a social coefficient metric for each social connectionrelative to the uploading user, a social affinity metric for each socialconnection relative to the uploading user, a social interaction recencymetric for each social connection relative to the uploading user, orlocation data associated with each social connection. It should beappreciated that many variations are possible.

FIG. 5 illustrates an example method 500 associated with providingobject recognition based on detecting and extracting media portions,according to an embodiment of the present disclosure. It should beappreciated that there can be additional, fewer, or alternative stepsperformed in similar or alternative orders, or in parallel, within thescope of the various embodiments unless otherwise stated.

At block 502, the example method 500 can receive a selection of animage. At block 504, the example method 500 can detect an objectincluded in the image. At block 506, the example method 500 can extract,from the image, an image portion that includes the object. At block 508,the example method 500 can provide the image portion for image analysisbased on one or more object recognition processes. At block 510, theexample method 500 can receive an identifier for the object. Theidentifier can be determined based on the one or more object recognitionprocesses being applied to the image portion.

FIG. 6 illustrates an example method 600 associated with providingobject recognition based on detecting and extracting media portions,according to an embodiment of the present disclosure. Again, it shouldbe appreciated that there can be additional, fewer, or alternative stepsperformed in similar or alternative orders, or in parallel, within thescope of the various embodiments unless otherwise stated.

At block 602, the example method 600 can present the image and theidentifier. At block 604, the example method 600 can provide one or moreoptions to modify at least one of the identifier or informationassociated with the image. At block 606, the example method 600 canreceive an upload command to upload the image. At block 608, the examplemethod 600 can transmit the image and the identifier subsequent toreceiving the upload command.

In some embodiments, the one or more facial recognition processes canutilize, at least in part, one or more people clustering processes. Insome embodiments, the identifier can be utilized, at least in part, todefine a set of images such that each image in the set includes arespective object associated with the identifier. The set of images can,for instance, form an album, which can be shared or synchronized amongone or more users.

It is contemplated that there can be many other uses, applications,features, possibilities, and/or variations associated with the variousembodiments of the present disclosure. For example, in some cases, usercan choose whether or not to opt-in to utilize the disclosed technology.The disclosed technology can also ensure that various privacy settingsand preferences are maintained and can prevent private information frombeing divulged. In another example, various embodiments of the presentdisclosure can learn, improve, and/or be refined over time.

Social Networking System—Example Implementation

FIG. 7 illustrates a network diagram of an example system 700 that canbe utilized in various scenarios, in accordance with an embodiment ofthe present disclosure. The system 700 includes one or more user devices710, one or more external systems 720, a social networking system (orservice) 730, and a network 750. In an embodiment, the social networkingservice, provider, and/or system discussed in connection with theembodiments described above may be implemented as the social networkingsystem 730. For purposes of illustration, the embodiment of the system700, shown by FIG. 7, includes a single external system 720 and a singleuser device 710. However, in other embodiments, the system 700 mayinclude more user devices 710 and/or more external systems 720. Incertain embodiments, the social networking system 730 is operated by asocial network provider, whereas the external systems 720 are separatefrom the social networking system 730 in that they may be operated bydifferent entities. In various embodiments, however, the socialnetworking system 730 and the external systems 720 operate inconjunction to provide social networking services to users (or members)of the social networking system 730. In this sense, the socialnetworking system 730 provides a platform or backbone, which othersystems, such as external systems 720, may use to provide socialnetworking services and functionalities to users across the Internet.

The user device 710 comprises one or more computing devices (or systems)that can receive input from a user and transmit and receive data via thenetwork 750. In one embodiment, the user device 710 is a conventionalcomputer system executing, for example, a Microsoft Windows compatibleoperating system (OS), Apple OS X, and/or a Linux distribution. Inanother embodiment, the user device 710 can be a computing device or adevice having computer functionality, such as a smart-phone, a tablet, apersonal digital assistant (PDA), a mobile telephone, a laptop computer,a wearable device (e.g., a pair of glasses, a watch, a bracelet, etc.),a camera, an appliance, etc. The user device 710 is configured tocommunicate via the network 750. The user device 710 can execute anapplication, for example, a browser application that allows a user ofthe user device 710 to interact with the social networking system 730.In another embodiment, the user device 710 interacts with the socialnetworking system 730 through an application programming interface (API)provided by the native operating system of the user device 710, such asiOS and ANDROID. The user device 710 is configured to communicate withthe external system 720 and the social networking system 730 via thenetwork 750, which may comprise any combination of local area and/orwide area networks, using wired and/or wireless communication systems.

In one embodiment, the network 750 uses standard communicationstechnologies and protocols. Thus, the network 750 can include linksusing technologies such as Ethernet, 702.11, worldwide interoperabilityfor microwave access (WiMAX), 3G, 4G, CDMA, GSM, LTE, digital subscriberline (DSL), etc. Similarly, the networking protocols used on the network750 can include multiprotocol label switching (MPLS), transmissioncontrol protocol/Internet protocol (TCP/IP), User Datagram Protocol(UDP), hypertext transport protocol (HTTP), simple mail transferprotocol (SMTP), file transfer protocol (FTP), and the like. The dataexchanged over the network 750 can be represented using technologiesand/or formats including hypertext markup language (HTML) and extensiblemarkup language (XML). In addition, all or some links can be encryptedusing conventional encryption technologies such as secure sockets layer(SSL), transport layer security (TLS), and Internet Protocol security(IPsec).

In one embodiment, the user device 710 may display content from theexternal system 720 and/or from the social networking system 730 byprocessing a markup language document 714 received from the externalsystem 720 and from the social networking system 730 using a browserapplication 712. The markup language document 714 identifies content andone or more instructions describing formatting or presentation of thecontent. By executing the instructions included in the markup languagedocument 714, the browser application 712 displays the identifiedcontent using the format or presentation described by the markuplanguage document 714. For example, the markup language document 714includes instructions for generating and displaying a web page havingmultiple frames that include text and/or image data retrieved from theexternal system 720 and the social networking system 730. In variousembodiments, the markup language document 714 comprises a data fileincluding extensible markup language (XML) data, extensible hypertextmarkup language (XHTML) data, or other markup language data.Additionally, the markup language document 714 may include JavaScriptObject Notation (JSON) data, JSON with padding (JSONP), and JavaScriptdata to facilitate data-interchange between the external system 720 andthe user device 710. The browser application 712 on the user device 710may use a JavaScript compiler to decode the markup language document714.

The markup language document 714 may also include, or link to,applications or application frameworks such as FLASH™ or Unity™applications, the SilverLight™ application framework, etc.

In one embodiment, the user device 710 also includes one or more cookies716 including data indicating whether a user of the user device 710 islogged into the social networking system 730, which may enablemodification of the data communicated from the social networking system730 to the user device 710.

The external system 720 includes one or more web servers that includeone or more web pages 722 a, 722 b, which are communicated to the userdevice 710 using the network 750. The external system 720 is separatefrom the social networking system 730. For example, the external system720 is associated with a first domain, while the social networkingsystem 730 is associated with a separate social networking domain. Webpages 722 a, 722 b, included in the external system 720, comprise markuplanguage documents 714 identifying content and including instructionsspecifying formatting or presentation of the identified content.

The social networking system 730 includes one or more computing devicesfor a social network, including a plurality of users, and providingusers of the social network with the ability to communicate and interactwith other users of the social network. In some instances, the socialnetwork can be represented by a graph, i.e., a data structure includingedges and nodes. Other data structures can also be used to represent thesocial network, including but not limited to databases, objects,classes, meta elements, files, or any other data structure. The socialnetworking system 730 may be administered, managed, or controlled by anoperator. The operator of the social networking system 730 may be ahuman being, an automated application, or a series of applications formanaging content, regulating policies, and collecting usage metricswithin the social networking system 730. Any type of operator may beused.

Users may join the social networking system 730 and then add connectionsto any number of other users of the social networking system 730 to whomthey desire to be connected. As used herein, the term “friend” refers toany other user of the social networking system 730 to whom a user hasformed a connection, association, or relationship via the socialnetworking system 730. For example, in an embodiment, if users in thesocial networking system 730 are represented as nodes in the socialgraph, the term “friend” can refer to an edge formed between anddirectly connecting two user nodes.

Connections may be added explicitly by a user or may be automaticallycreated by the social networking system 730 based on commoncharacteristics of the users (e.g., users who are alumni of the sameeducational institution). For example, a first user specifically selectsa particular other user to be a friend. Connections in the socialnetworking system 730 are usually in both directions, but need not be,so the terms “user” and “friend” depend on the frame of reference.Connections between users of the social networking system 730 areusually bilateral (“two-way”), or “mutual,” but connections may also beunilateral, or “one-way.” For example, if Bob and Joe are both users ofthe social networking system 730 and connected to each other, Bob andJoe are each other's connections. If, on the other hand, Bob wishes toconnect to Joe to view data communicated to the social networking system730 by Joe, but Joe does not wish to form a mutual connection, aunilateral connection may be established. The connection between usersmay be a direct connection; however, some embodiments of the socialnetworking system 730 allow the connection to be indirect via one ormore levels of connections or degrees of separation.

In addition to establishing and maintaining connections between usersand allowing interactions between users, the social networking system730 provides users with the ability to take actions on various types ofitems supported by the social networking system 730. These items mayinclude groups or networks (i.e., social networks of people, entities,and concepts) to which users of the social networking system 730 maybelong, events or calendar entries in which a user might be interested,computer-based applications that a user may use via the socialnetworking system 730, transactions that allow users to buy or sellitems via services provided by or through the social networking system730, and interactions with advertisements that a user may perform on oroff the social networking system 730. These are just a few examples ofthe items upon which a user may act on the social networking system 730,and many others are possible. A user may interact with anything that iscapable of being represented in the social networking system 730 or inthe external system 720, separate from the social networking system 730,or coupled to the social networking system 730 via the network 750.

The social networking system 730 is also capable of linking a variety ofentities. For example, the social networking system 730 enables users tointeract with each other as well as external systems 720 or otherentities through an API, a web service, or other communication channels.The social networking system 730 generates and maintains the “socialgraph” comprising a plurality of nodes interconnected by a plurality ofedges. Each node in the social graph may represent an entity that canact on another node and/or that can be acted on by another node. Thesocial graph may include various types of nodes. Examples of types ofnodes include users, non-person entities, content items, web pages,groups, activities, messages, concepts, and any other things that can berepresented by an object in the social networking system 730. An edgebetween two nodes in the social graph may represent a particular kind ofconnection, or association, between the two nodes, which may result fromnode relationships or from an action that was performed by one of thenodes on the other node. In some cases, the edges between nodes can beweighted. The weight of an edge can represent an attribute associatedwith the edge, such as a strength of the connection or associationbetween nodes. Different types of edges can be provided with differentweights. For example, an edge created when one user “likes” another usermay be given one weight, while an edge created when a user befriendsanother user may be given a different weight.

As an example, when a first user identifies a second user as a friend,an edge in the social graph is generated connecting a node representingthe first user and a second node representing the second user. Asvarious nodes relate or interact with each other, the social networkingsystem 730 modifies edges connecting the various nodes to reflect therelationships and interactions.

The social networking system 730 also includes user-generated content,which enhances a user's interactions with the social networking system730. User-generated content may include anything a user can add, upload,send, or “post” to the social networking system 730. For example, a usercommunicates posts to the social networking system 730 from a userdevice 710. Posts may include data such as status updates or othertextual data, location information, images such as photos, videos,links, music or other similar data and/or media. Content may also beadded to the social networking system 730 by a third party. Content“items” are represented as objects in the social networking system 730.In this way, users of the social networking system 730 are encouraged tocommunicate with each other by posting text and content items of varioustypes of media through various communication channels. Suchcommunication increases the interaction of users with each other andincreases the frequency with which users interact with the socialnetworking system 730.

The social networking system 730 includes a web server 732, an APIrequest server 734, a user profile store 736, a connection store 738, anaction logger 740, an activity log 742, and an authorization server 744.In an embodiment of the invention, the social networking system 730 mayinclude additional, fewer, or different components for variousapplications. Other components, such as network interfaces, securitymechanisms, load balancers, failover servers, management and networkoperations consoles, and the like are not shown so as to not obscure thedetails of the system.

The user profile store 736 maintains information about user accounts,including biographic, demographic, and other types of descriptiveinformation, such as work experience, educational history, hobbies orpreferences, location, and the like that has been declared by users orinferred by the social networking system 730. This information is storedin the user profile store 736 such that each user is uniquelyidentified. The social networking system 730 also stores data describingone or more connections between different users in the connection store738. The connection information may indicate users who have similar orcommon work experience, group memberships, hobbies, or educationalhistory. Additionally, the social networking system 730 includesuser-defined connections between different users, allowing users tospecify their relationships with other users. For example, user-definedconnections allow users to generate relationships with other users thatparallel the users' real-life relationships, such as friends,co-workers, partners, and so forth. Users may select from predefinedtypes of connections, or define their own connection types as needed.Connections with other nodes in the social networking system 730, suchas non-person entities, buckets, cluster centers, images, interests,pages, external systems, concepts, and the like are also stored in theconnection store 738.

The social networking system 730 maintains data about objects with whicha user may interact. To maintain this data, the user profile store 736and the connection store 738 store instances of the corresponding typeof objects maintained by the social networking system 730. Each objecttype has information fields that are suitable for storing informationappropriate to the type of object. For example, the user profile store736 contains data structures with fields suitable for describing auser's account and information related to a user's account. When a newobject of a particular type is created, the social networking system 730initializes a new data structure of the corresponding type, assigns aunique object identifier to it, and begins to add data to the object asneeded. This might occur, for example, when a user becomes a user of thesocial networking system 730, the social networking system 730 generatesa new instance of a user profile in the user profile store 736, assignsa unique identifier to the user account, and begins to populate thefields of the user account with information provided by the user.

The connection store 738 includes data structures suitable fordescribing a user's connections to other users, connections to externalsystems 720 or connections to other entities. The connection store 738may also associate a connection type with a user's connections, whichmay be used in conjunction with the user's privacy setting to regulateaccess to information about the user. In an embodiment of the invention,the user profile store 736 and the connection store 738 may beimplemented as a federated database.

Data stored in the connection store 738, the user profile store 736, andthe activity log 742 enables the social networking system 730 togenerate the social graph that uses nodes to identify various objectsand edges connecting nodes to identify relationships between differentobjects. For example, if a first user establishes a connection with asecond user in the social networking system 730, user accounts of thefirst user and the second user from the user profile store 736 may actas nodes in the social graph. The connection between the first user andthe second user stored by the connection store 738 is an edge betweenthe nodes associated with the first user and the second user. Continuingthis example, the second user may then send the first user a messagewithin the social networking system 730. The action of sending themessage, which may be stored, is another edge between the two nodes inthe social graph representing the first user and the second user.Additionally, the message itself may be identified and included in thesocial graph as another node connected to the nodes representing thefirst user and the second user.

In another example, a first user may tag a second user in an image thatis maintained by the social networking system 730 (or, alternatively, inan image maintained by another system outside of the social networkingsystem 730). The image may itself be represented as a node in the socialnetworking system 730. This tagging action may create edges between thefirst user and the second user as well as create an edge between each ofthe users and the image, which is also a node in the social graph. Inyet another example, if a user confirms attending an event, the user andthe event are nodes obtained from the user profile store 736, where theattendance of the event is an edge between the nodes that may beretrieved from the activity log 742. By generating and maintaining thesocial graph, the social networking system 730 includes data describingmany different types of objects and the interactions and connectionsamong those objects, providing a rich source of socially relevantinformation.

The web server 732 links the social networking system 730 to one or moreuser devices 710 and/or one or more external systems 720 via the network750. The web server 732 serves web pages, as well as other web-relatedcontent, such as Java, JavaScript, Flash, XML, and so forth. The webserver 732 may include a mail server or other messaging functionalityfor receiving and routing messages between the social networking system730 and one or more user devices 710. The messages can be instantmessages, queued messages (e.g., email), text and SMS messages, or anyother suitable messaging format.

The API request server 734 allows one or more external systems 720 anduser devices 710 to call access information from the social networkingsystem 730 by calling one or more API functions. The API request server734 may also allow external systems 720 to send information to thesocial networking system 730 by calling APIs. The external system 720,in one embodiment, sends an API request to the social networking system730 via the network 750, and the API request server 734 receives the APIrequest. The API request server 734 processes the request by calling anAPI associated with the API request to generate an appropriate response,which the API request server 734 communicates to the external system 720via the network 750. For example, responsive to an API request, the APIrequest server 734 collects data associated with a user, such as theuser's connections that have logged into the external system 720, andcommunicates the collected data to the external system 720. In anotherembodiment, the user device 710 communicates with the social networkingsystem 730 via APIs in the same manner as external systems 720.

The action logger 740 is capable of receiving communications from theweb server 732 about user actions on and/or off the social networkingsystem 730. The action logger 740 populates the activity log 742 withinformation about user actions, enabling the social networking system730 to discover various actions taken by its users within the socialnetworking system 730 and outside of the social networking system 730.Any action that a particular user takes with respect to another node onthe social networking system 730 may be associated with each user'saccount, through information maintained in the activity log 742 or in asimilar database or other data repository. Examples of actions taken bya user within the social networking system 730 that are identified andstored may include, for example, adding a connection to another user,sending a message to another user, reading a message from another user,viewing content associated with another user, attending an event postedby another user, posting an image, attempting to post an image, or otheractions interacting with another user or another object. When a usertakes an action within the social networking system 730, the action isrecorded in the activity log 742. In one embodiment, the socialnetworking system 730 maintains the activity log 742 as a database ofentries. When an action is taken within the social networking system730, an entry for the action is added to the activity log 742. Theactivity log 742 may be referred to as an action log.

Additionally, user actions may be associated with concepts and actionsthat occur within an entity outside of the social networking system 730,such as an external system 720 that is separate from the socialnetworking system 730. For example, the action logger 740 may receivedata describing a user's interaction with an external system 720 fromthe web server 732. In this example, the external system 720 reports auser's interaction according to structured actions and objects in thesocial graph.

Other examples of actions where a user interacts with an external system720 include a user expressing an interest in an external system 720 oranother entity, a user posting a comment to the social networking system730 that discusses an external system 720 or a web page 722 a within theexternal system 720, a user posting to the social networking system 730a Uniform Resource Locator (URL) or other identifier associated with anexternal system 720, a user attending an event associated with anexternal system 720, or any other action by a user that is related to anexternal system 720. Thus, the activity log 742 may include actionsdescribing interactions between a user of the social networking system730 and an external system 720 that is separate from the socialnetworking system 730.

The authorization server 744 enforces one or more privacy settings ofthe users of the social networking system 730. A privacy setting of auser determines how particular information associated with a user can beshared. The privacy setting comprises the specification of particularinformation associated with a user and the specification of the entityor entities with whom the information can be shared. Examples ofentities with which information can be shared may include other users,applications, external systems 720, or any entity that can potentiallyaccess the information. The information that can be shared by a usercomprises user account information, such as profile photos, phonenumbers associated with the user, user's connections, actions taken bythe user such as adding a connection, changing user profile information,and the like.

The privacy setting specification may be provided at different levels ofgranularity. For example, the privacy setting may identify specificinformation to be shared with other users; the privacy settingidentifies a work phone number or a specific set of related information,such as, personal information including profile photo, home phonenumber, and status. Alternatively, the privacy setting may apply to allthe information associated with the user. The specification of the setof entities that can access particular information can also be specifiedat various levels of granularity. Various sets of entities with whichinformation can be shared may include, for example, all friends of theuser, all friends of friends, all applications, or all external systems720. One embodiment allows the specification of the set of entities tocomprise an enumeration of entities. For example, the user may provide alist of external systems 720 that are allowed to access certaininformation. Another embodiment allows the specification to comprise aset of entities along with exceptions that are not allowed to access theinformation. For example, a user may allow all external systems 720 toaccess the user's work information, but specify a list of externalsystems 720 that are not allowed to access the work information. Certainembodiments call the list of exceptions that are not allowed to accesscertain information a “block list”. External systems 720 belonging to ablock list specified by a user are blocked from accessing theinformation specified in the privacy setting. Various combinations ofgranularity of specification of information, and granularity ofspecification of entities, with which information is shared arepossible. For example, all personal information may be shared withfriends whereas all work information may be shared with friends offriends.

The authorization server 744 contains logic to determine if certaininformation associated with a user can be accessed by a user's friends,external systems 720, and/or other applications and entities. Theexternal system 720 may need authorization from the authorization server744 to access the user's more private and sensitive information, such asthe user's work phone number. Based on the user's privacy settings, theauthorization server 744 determines if another user, the external system720, an application, or another entity is allowed to access informationassociated with the user, including information about actions taken bythe user.

In some embodiments, the user device 710 can include a media portionrecognition module 718. The media portion recognition module 718 can,for example, be implemented as the media portion recognition module 102of FIG. 1. As discussed previously, it should be appreciated that therecan be many variations or other possibilities. For example, in someinstances, the media portion recognition module 718 (or at least aportion thereof) can be included in the social networking system 730.Other features of the media portion recognition module 718 are discussedherein in connection with the media portion recognition module 102.

Hardware Implementation

The foregoing processes and features can be implemented by a widevariety of machine and computer system architectures and in a widevariety of network and computing environments. FIG. 8 illustrates anexample of a computer system 800 that may be used to implement one ormore of the embodiments described herein in accordance with anembodiment of the invention. The computer system 800 includes sets ofinstructions for causing the computer system 800 to perform theprocesses and features discussed herein. The computer system 800 may beconnected (e.g., networked) to other machines. In a networkeddeployment, the computer system 800 may operate in the capacity of aserver machine or a client machine in a client-server networkenvironment, or as a peer machine in a peer-to-peer (or distributed)network environment. In an embodiment of the invention, the computersystem 800 may be the social networking system 730, the user device 710,and the external system 820, or a component thereof. In an embodiment ofthe invention, the computer system 800 may be one server among many thatconstitutes all or part of the social networking system 730.

The computer system 800 includes a processor 802, a cache 804, and oneor more executable modules and drivers, stored on a computer-readablemedium, directed to the processes and features described herein.Additionally, the computer system 800 includes a high performanceinput/output (I/O) bus 806 and a standard I/O bus 808. A host bridge 810couples processor 802 to high performance I/O bus 806, whereas I/O busbridge 812 couples the two buses 806 and 808 to each other. A systemmemory 814 and one or more network interfaces 816 couple to highperformance I/O bus 806. The computer system 800 may further includevideo memory and a display device coupled to the video memory (notshown). Mass storage 818 and I/O ports 820 couple to the standard I/Obus 808. The computer system 800 may optionally include a keyboard andpointing device, a display device, or other input/output devices (notshown) coupled to the standard I/O bus 808. Collectively, these elementsare intended to represent a broad category of computer hardware systems,including but not limited to computer systems based on thex86-compatible processors manufactured by Intel Corporation of SantaClara, Calif., and the x86-compatible processors manufactured byAdvanced Micro Devices (AMD), Inc., of Sunnyvale, Calif., as well as anyother suitable processor.

An operating system manages and controls the operation of the computersystem 800, including the input and output of data to and from softwareapplications (not shown). The operating system provides an interfacebetween the software applications being executed on the system and thehardware components of the system. Any suitable operating system may beused, such as the LINUX Operating System, the Apple Macintosh OperatingSystem, available from Apple Computer Inc. of Cupertino, Calif., UNIXoperating systems, Microsoft® Windows® operating systems, BSD operatingsystems, and the like. Other implementations are possible.

The elements of the computer system 800 are described in greater detailbelow. In particular, the network interface 816 provides communicationbetween the computer system 800 and any of a wide range of networks,such as an Ethernet (e.g., IEEE 802.3) network, a backplane, etc. Themass storage 818 provides permanent storage for the data and programminginstructions to perform the above-described processes and featuresimplemented by the respective computing systems identified above,whereas the system memory 814 (e.g., DRAM) provides temporary storagefor the data and programming instructions when executed by the processor802. The I/O ports 820 may be one or more serial and/or parallelcommunication ports that provide communication between additionalperipheral devices, which may be coupled to the computer system 800.

The computer system 800 may include a variety of system architectures,and various components of the computer system 800 may be rearranged. Forexample, the cache 804 may be on-chip with processor 802. Alternatively,the cache 804 and the processor 802 may be packed together as a“processor module”, with processor 802 being referred to as the“processor core”. Furthermore, certain embodiments of the invention mayneither require nor include all of the above components. For example,peripheral devices coupled to the standard I/O bus 808 may couple to thehigh performance I/O bus 806. In addition, in some embodiments, only asingle bus may exist, with the components of the computer system 800being coupled to the single bus. Moreover, the computer system 800 mayinclude additional components, such as additional processors, storagedevices, or memories.

In general, the processes and features described herein may beimplemented as part of an operating system or a specific application,component, program, object, module, or series of instructions referredto as “programs”. For example, one or more programs may be used toexecute specific processes described herein. The programs typicallycomprise one or more instructions in various memory and storage devicesin the computer system 800 that, when read and executed by one or moreprocessors, cause the computer system 800 to perform operations toexecute the processes and features described herein. The processes andfeatures described herein may be implemented in software, firmware,hardware (e.g., an application specific integrated circuit), or anycombination thereof.

In one implementation, the processes and features described herein areimplemented as a series of executable modules run by the computer system800, individually or collectively in a distributed computingenvironment. The foregoing modules may be realized by hardware,executable modules stored on a computer-readable medium (ormachine-readable medium), or a combination of both. For example, themodules may comprise a plurality or series of instructions to beexecuted by a processor in a hardware system, such as the processor 802.Initially, the series of instructions may be stored on a storage device,such as the mass storage 818. However, the series of instructions can bestored on any suitable computer readable storage medium. Furthermore,the series of instructions need not be stored locally, and could bereceived from a remote storage device, such as a server on a network,via the network interface 816. The instructions are copied from thestorage device, such as the mass storage 818, into the system memory 814and then accessed and executed by the processor 802. In variousimplementations, a module or modules can be executed by a processor ormultiple processors in one or multiple locations, such as multipleservers in a parallel processing environment.

Examples of computer-readable media include, but are not limited to,recordable type media such as volatile and non-volatile memory devices;solid state memories; floppy and other removable disks; hard diskdrives; magnetic media; optical disks (e.g., Compact Disk Read-OnlyMemory (CD ROMS), Digital Versatile Disks (DVDs)); other similarnon-transitory (or transitory), tangible (or non-tangible) storagemedium; or any type of medium suitable for storing, encoding, orcarrying a series of instructions for execution by the computer system800 to perform any one or more of the processes and features describedherein.

For purposes of explanation, numerous specific details are set forth inorder to provide a thorough understanding of the description. It will beapparent, however, to one skilled in the art that embodiments of thedisclosure can be practiced without these specific details. In someinstances, modules, structures, processes, features, and devices areshown in block diagram form in order to avoid obscuring the description.In other instances, functional block diagrams and flow diagrams areshown to represent data and logic flows. The components of blockdiagrams and flow diagrams (e.g., modules, blocks, structures, devices,features, etc.) may be variously combined, separated, removed,reordered, and replaced in a manner other than as expressly describedand depicted herein.

Reference in this specification to “one embodiment”, “an embodiment”,“other embodiments”, “one series of embodiments”, “some embodiments”,“various embodiments”, or the like means that a particular feature,design, structure, or characteristic described in connection with theembodiment is included in at least one embodiment of the disclosure. Theappearances of, for example, the phrase “in one embodiment” or “in anembodiment” in various places in the specification are not necessarilyall referring to the same embodiment, nor are separate or alternativeembodiments mutually exclusive of other embodiments. Moreover, whetheror not there is express reference to an “embodiment” or the like,various features are described, which may be variously combined andincluded in some embodiments, but also variously omitted in otherembodiments. Similarly, various features are described that may bepreferences or requirements for some embodiments, but not otherembodiments.

The language used herein has been principally selected for readabilityand instructional purposes, and it may not have been selected todelineate or circumscribe the inventive subject matter. It is thereforeintended that the scope of the invention be limited not by this detaileddescription, but rather by any claims that issue on an application basedhereon. Accordingly, the disclosure of the embodiments of the inventionis intended to be illustrative, but not limiting, of the scope of theinvention, which is set forth in the following claims.

What is claimed is:
 1. A computer-implemented method comprising:receiving, by a computing system, a selection of an image by a user;receiving, by the computing system, an identifier for an objectassociated with an image portion of the image, the image portion of theimage provided to one or more servers remote from the computing systemto generate the identifier based on an object recognition process towhich the image portion is applied; presenting, by the computing system,the image and the identifier to the user; and transmitting, by thecomputing system, the image and the identifier to a networking system inresponse to a command by the user.
 2. The computer-implemented method ofclaim 1, further comprising: detecting the object in the image.
 3. Thecomputer-implemented method of claim 1, wherein the image portioncomprises a set of pixels associated with the object.
 4. Thecomputer-implemented method of claim 1, further comprising: providingthe user an option to modify the identifier.
 5. The computer-implementedmethod of claim 1, further comprising: determining a location of theobject in the image; and overlaying the identifier on the image based onthe location of the object in the image.
 6. The computer-implementedmethod of claim 1, further comprising: detecting the object associatedwith the image portion of the image; detecting a second objectassociated with a second image portion of the image; and providing inconjunction the image portion and the second image portion to the one ormore servers remote from the computing system to generate the identifierand a second identifier based on the object recognition process to whichthe image portion and the second image portion are applied.
 7. Thecomputer-implemented method of claim 1, wherein the object comprises aface of a person represented in the image, the object recognitionprocess comprises a facial recognition process, and the identifiercomprises a name associated with the person.
 8. The computer-implementedmethod of claim 7, wherein the facial recognition process is based atleast in part on a people clustering process.
 9. Thecomputer-implemented method of claim 7, wherein the user is associatedwith a set of social connections via the networking system and thefacial recognition process is based at least in part on one or more facemodels associated with a subset of social connections out of the set ofsocial connections.
 10. The computer-implemented method of claim 9,wherein the subset of social connections is associated with a ranking ofthe set of social connections, the ranking based on at least one of asocial coefficient metric, a social affinity metric, a socialinteraction recency metric, and location data.
 11. A system comprising:at least one processor; and a memory storing instructions that, whenexecuted by the at least one processor, cause the system to perform:receiving a selection of an image by a user; receiving an identifier foran object associated with an image portion of the image, the imageportion of the image provided to one or more servers remote from thecomputing system to generate the identifier based on an objectrecognition process to which the image portion is applied; presentingthe image and the identifier to the user; and transmitting the image andthe identifier to a networking system in response to a command by theuser.
 12. The system of claim 11, wherein the instructions cause thesystem to further perform: detecting the object in the image.
 13. Thesystem of claim 11, wherein the image portion comprises a set of pixelsassociated with the object.
 14. The system of claim 11, wherein theinstructions cause the system to further perform: providing the user anoption to modify the identifier.
 15. The system of claim 11, wherein theinstructions cause the system to further perform: determining a locationof the object in the image; and overlaying the identifier on the imagebased on the location of the object in the image.
 16. A non-transitorycomputer-readable storage medium including instructions that, whenexecuted by at least one processor of a computing system, cause thecomputing system to perform: receiving a selection of an image by auser; receiving an identifier for an object associated with an imageportion of the image, the image portion of the image provided to one ormore servers remote from the computing system to generate the identifierbased on an object recognition process to which the image portion isapplied; presenting the image and the identifier to the user; andtransmitting the image and the identifier to a networking system inresponse to a command by the user.
 17. The non-transitorycomputer-readable storage medium of claim 16, wherein the instructionscause the computing system to further perform: detecting the object inthe image.
 18. The non-transitory computer-readable storage medium ofclaim 16, wherein the image portion comprises a set of pixels associatedwith the object.
 19. The non-transitory computer-readable storage mediumof claim 16, wherein the instructions cause the computing system tofurther perform: providing the user an option to modify the identifier.20. The non-transitory computer-readable storage medium of claim 16,wherein the instructions cause the computing system to further perform:determining a location of the object in the image; and overlaying theidentifier on the image based on the location of the object in theimage.